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Record W2587625487 · doi:10.7202/1038690ar

Quand les médias traduisent la crise : les métaphores utilisées par la presse généraliste pendant la crise des subprimes

2017· article· fr· W2587625487 on OpenAlexaffvenueabout
Pier-Pascale Boulanger

Bibliographic record

VenueMeta Journal des traducteurs · 2017
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Dans la couverture médiatique de la crise des prêts hypothécaires à risque (dits subprimes ) qui a éclaté en août 2007, la traduction s’est trouvée mobilisée du fait que les déclencheurs de cette crise étaient d’origine américaine et ont dû être expliqués par les journalistes canadiens aux lectorats anglophones et francophones. Pour présenter avec une économie de moyens des concepts compliqués et souligner la gravité de la situation, les journalistes ont recouru aux métaphores de l’accident, du cataclysme, de la catastrophe et de l’épidémie. Après analyse des métaphores conceptuelles trouvées dans La Presse, Le Devoir, The Toronto Star et The Globe and Mail, l’article démontre que, loin d’être banales, elles confortent une idéologie néolibérale de l’économie.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0070.007
Scholarly communication0.0080.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.152
GPT teacher head0.333
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2017
Admission routes3
Has abstractyes

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